{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T15:09:43Z","timestamp":1784732983603,"version":"3.55.0"},"reference-count":70,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2019,12,16]],"date-time":"2019-12-16T00:00:00Z","timestamp":1576454400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41971228"],"award-info":[{"award-number":["41971228"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41371190"],"award-info":[{"award-number":["41371190"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012165","name":"Key Technologies Research and Development Program","doi-asserted-by":"publisher","award":["2017YFC0505200"],"award-info":[{"award-number":["2017YFC0505200"]}],"id":[{"id":"10.13039\/501100012165","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Moderate Resolution Imaging Spectroradiometer (MODIS) has been widely used for wildfire occurrence and distribution detecting and fire risk assessments. Compared with its commission error, the omission error of MODIS wildfire detection has been revealed as a much more challenging, unsolved issue, and ground-level environmental factors influencing the detection capacity are also variable. This study compared the multiple MODIS fire products and the records of ground wildfire investigations during December 2002\u2013November 2015 in Yunnan Province, Southwest China, in an attempt to reveal the difference in the spatiotemporal patterns of regional wildfire detected by the two approaches, to estimate the omission error of MODIS fire products based on confirmed ground wildfire records, and to explore how instantaneous and local environmental factors influenced the wildfire detection probability of MODIS. The results indicated that across the province, the total number of wildfire events recorded by MODIS was at least twice as many as that in the ground records, while the wildfire distribution patterns revealed by the two approaches were inconsistent. For the 5145 confirmed ground records, however, only 11.10% of them could be detected using multiple MODIS fire products (i.e., MOD14A1, MYD14A1, and MCD64A1). Opposing trends during the studied period were found between the yearly occurrence of ground-based wildfire records and the corresponding proportion detected by MODIS. Moreover, the wildfire detection proportion by MODIS was 11.36% in forest, 9.58% in shrubs, and 5.56% in grassland, respectively. Random forest modeling suggested that fire size was a primary limiting factor for MODIS fire detecting capacity, where a small fire size could likely result in MODIS omission errors at a threshold of 1 ha, while MODIS had a 50% probability of detecting a wildfire whose size was at least 18 ha. Aside from fire size, the wildfire detection probability of MODIS was also markedly influenced by weather factors, especially the daily relative humidity and the daily wind speed, and the altitude of wildfire occurrence. Considering the environmental factors\u2019 contribution to the omission error in MODIS wildfire detection, we emphasized the importance of attention to the local conditions as well as ground inspection in practical wildfire monitoring and management and global wildfire simulations.<\/jats:p>","DOI":"10.3390\/rs11243031","type":"journal-article","created":{"date-parts":[[2019,12,17]],"date-time":"2019-12-17T02:59:01Z","timestamp":1576551541000},"page":"3031","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":65,"title":["Wildfire Detection Probability of MODIS Fire Products under the Constraint of Environmental Factors: A Study Based on Confirmed Ground Wildfire Records"],"prefix":"10.3390","volume":"11","author":[{"given":"Lingxiao","family":"Ying","sequence":"first","affiliation":[{"name":"Ministry-of-Education (MOE) Key Laboratory for Earth Surface Processes, Institute of Ecology, College of Urban &amp; Environmental Sciences, Peking University, Yiheyuan Road 5, Beijing 100871, China"},{"name":"Key Laboratory of Land Consolidation and Rehabilitation, Land Consolidation and Rehabilitation Center, Ministry of Natural Resources, Guanyingyuan West District 37, Beijing 100035, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zehao","family":"Shen","sequence":"additional","affiliation":[{"name":"Ministry-of-Education (MOE) Key Laboratory for Earth Surface Processes, Institute of Ecology, College of Urban &amp; Environmental Sciences, Peking University, Yiheyuan Road 5, Beijing 100871, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingzheng","family":"Yang","sequence":"additional","affiliation":[{"name":"Ministry-of-Education (MOE) Key Laboratory for Earth Surface Processes, Institute of Ecology, College of Urban &amp; Environmental Sciences, Peking University, Yiheyuan Road 5, Beijing 100871, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shilong","family":"Piao","sequence":"additional","affiliation":[{"name":"Ministry-of-Education (MOE) Key Laboratory for Earth Surface Processes, Institute of Ecology, College of Urban &amp; Environmental Sciences, Peking University, Yiheyuan Road 5, Beijing 100871, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1126\/science.1163886","article-title":"Fire in the Earth system","volume":"324","author":"Bowman","year":"2009","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1356","DOI":"10.1126\/science.aal4108","article-title":"A human-driven decline in global burned area","volume":"356","author":"Andela","year":"2017","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2755","DOI":"10.1111\/jbi.13441","article-title":"The compounding consequences of wildfire and climate change for a high-elevation wildflower (Saxifraga austromontana)","volume":"45","author":"Bloom","year":"2018","journal-title":"J. Biogeogr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"e02091","DOI":"10.1002\/ecs2.2091","article-title":"Fire enhances the complexity of forest structure in alpine treeline ecotones","volume":"9","author":"Cansler","year":"2018","journal-title":"Ecosphere"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.atmosenv.2017.10.024","article-title":"Seasonal impact of regional outdoor biomass burning on air pollution in three Indian cities: Delhi, Bengaluru, and Pune","volume":"172","author":"Liu","year":"2018","journal-title":"Atmos. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1563","DOI":"10.1080\/19475705.2019.1578271","article-title":"Integrated approach of RUSLE, GIS and ESA Sentinel-2 satellite data for post-fire soil erosion assessment in Basilicata region (Southern Italy)","volume":"10","author":"Lanorte","year":"2019","journal-title":"Geomat. Nat. Haz. Risk"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1007\/s10584-017-1925-0","article-title":"Divergent trends in ecosystem services under different climate-management futures in a fire-prone forest landscape","volume":"142","author":"Halofsky","year":"2017","journal-title":"Clim. Chang."},{"key":"ref_8","first-page":"140","article-title":"Desa\u2019a national forest reserve susceptibility to fire under climate change","volume":"15","author":"Abrha","year":"2019","journal-title":"For. Sci. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1071\/WF13002","article-title":"Characterising weather patterns associated with fire in a seasonally dry tropical forest in southern India","volume":"23","author":"Mondal","year":"2014","journal-title":"Int. J. Wildland Fire"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1016\/j.foreco.2018.05.020","article-title":"Forest fire characteristics in China: Spatial patterns and determinants with thresholds","volume":"424","author":"Ying","year":"2018","journal-title":"For. Ecol. Manag."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"34","DOI":"10.4996\/fireecology.1301034","article-title":"Carbon emissions during wildland fire on a North American temperate peatland","volume":"13","author":"Mickler","year":"2017","journal-title":"Fire Ecol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2931","DOI":"10.1111\/gcb.14709","article-title":"Effects of climate and land-use change scenarios on fire probability during the 21st century in the Brazilian Amazon","volume":"25","author":"Fonseca","year":"2019","journal-title":"Glob. Chang. Biol."},{"key":"ref_13","first-page":"305","article-title":"Validation of MODIS active fire detection products derived from two algorithms","volume":"9","author":"Morisette","year":"2004","journal-title":"Earth Interact."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.1109\/TGRS.2008.2009000","article-title":"Southern Africa validation of the MODIS, L3JRC, and GlobCarbon burned\u2013area products","volume":"47","author":"Roy","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"5076","DOI":"10.1002\/ece3.877","article-title":"Climate change and fire effects on a prairie\u2013woodland ecotone: Projecting species range shifts with a dynamic global vegetation model","volume":"3","author":"King","year":"2013","journal-title":"Ecol. Evol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1071\/WF15121","article-title":"What drives forest fire in Fujian, China? Evidence from logistic regression and Random Forests","volume":"25","author":"Guo","year":"2016","journal-title":"Int. J. Wildland Fire"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.apgeog.2017.05.013","article-title":"Mapping fire regimes in China using MODIS active fire and burned area data","volume":"85","author":"Chen","year":"2017","journal-title":"Appl. Geogr."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0034-4257(03)00184-6","article-title":"An enhanced contextual fire detection algorithm for MODIS","volume":"87","author":"Giglio","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.rse.2005.04.007","article-title":"Prototyping a global algorithm for systematic fire\u2013affected area mapping using MODIS time series data","volume":"97","author":"Roy","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"6950","DOI":"10.3390\/rs70606950","article-title":"Standardized time\u2013series and interannual phenological deviation: New techniques for burned\u2013area detection using long\u2013term MODIS\u2013NBR dataset","volume":"7","author":"Silva","year":"2015","journal-title":"Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1016\/j.rse.2016.09.016","article-title":"A stratified random sampling design in space and time for regional to global scale burned area product validation","volume":"186","author":"Boschetti","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1080\/17538947.2018.1433727","article-title":"Spatial and temporal intercomparison of four global burned area products","volume":"12","author":"Humber","year":"2019","journal-title":"Int. J. Digit. Earth"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.rse.2012.12.004","article-title":"Strengths and weaknesses of MODIS hotspots to characterize global fire occurrence","volume":"131","author":"Hantson","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2711","DOI":"10.1016\/j.rse.2008.01.005","article-title":"Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data","volume":"112","author":"Schroeder","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.rse.2016.02.054","article-title":"The collection 6 MODIS active fire detection algorithm and fire products","volume":"178","author":"Giglio","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"5668","DOI":"10.4028\/www.scientific.net\/AMR.518-523.5668","article-title":"Advance in monitoring forest fire in China based on multi-satellite data","volume":"518\u2013523","author":"Zhang","year":"2012","journal-title":"Adv. Mater. Res."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Fornacca, D., Ren, G., and Xiao, W. (2017). Performance of three MODIS fire products (MCD45A1, MCD64A1, MCD14ML), and ESA Fire_CCI in a mountainous area of Northwest Yunnan, China, characterized by frequent small fires. Remote Sens., 9.","DOI":"10.3390\/rs9111131"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Sharma, A., and Wang, J. (2017). Intercomparison of MODIS and VIIRS fire products in Khanty-Mansiysk Russia: Implications for characterizing gas flaring from space. Atmosphere, 8.","DOI":"10.20944\/preprints201705.0051.v1"},{"key":"ref_29","first-page":"127","article-title":"The comparison of remote sensing aerosol optical depth from MODIS data and ground sun\u2013photometer observations","volume":"13","author":"Mao","year":"2002","journal-title":"J. Appl. Meteor. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"5297","DOI":"10.1080\/01431160410001720180","article-title":"Comparison of MODIS broadband albedo over an agricultural site with ground measurements and values derived from Earth observation data at a range of spatial scales","volume":"25","author":"Disney","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.rse.2007.01.004","article-title":"Cross\u2013scalar satellite phenology from ground, Landsat, and MODIS data","volume":"109","author":"Fisher","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4626","DOI":"10.1002\/hyp.10123","article-title":"Snow cover estimation using blended MODIS and AMSR\u2013E data for improved watershed\u2013scale spring streamflow simulation in Quebec, Canada","volume":"28","author":"Bergeron","year":"2014","journal-title":"Hydrol. Process."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1177\/2053019615588790","article-title":"Satellite versus ground-based estimates of burned area: A comparison between MODIS based burned area and fire agency reports over North America in 2007","volume":"3","author":"Mangeon","year":"2016","journal-title":"Anthropol. Rev."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1071\/WF14031","article-title":"Comparison of forest burned areas in mainland China derived from MCD45A1 and data recorded in yearbooks from 2001 to 2011","volume":"24","author":"Li","year":"2015","journal-title":"Int. J. Wildland Fire"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.rse.2018.10.028","article-title":"Detection rates and biases of fire observations from MODIS and agency reports in the conterminous United States","volume":"220","author":"Fusco","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.foreco.2015.06.016","article-title":"Early post-fire regeneration of a fire-prone subtropical mixed Yunnan pine forest in Southwest China: Effects of pre-fire vegetation, fire severity and topographic factors","volume":"356","author":"Han","year":"2015","journal-title":"For. Ecol. Manag."},{"key":"ref_37","unstructured":"(2019, December 14). National Meteorological Information Center of China. Available online: http:\/\/data.cma.cn\/en."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"813","DOI":"10.1023\/B:BIOC.0000011728.46362.3c","article-title":"Biodiversity and biodiversity conservation in Yunnan, China","volume":"13","author":"Yang","year":"2004","journal-title":"Biodivers. Conserv."},{"key":"ref_39","first-page":"197","article-title":"The climatic dividing line between SW and SE monsoons and their differences in climatology and ecology in Yunnan Province of China (Climates, geoecology and agriculture in South China (II))","volume":"38","author":"Zhang","year":"1988","journal-title":"Climatol. Notes"},{"key":"ref_40","first-page":"527","article-title":"Changes of the boundary between the South Asian and East Asian tropical summer monsoon subsystems","volume":"25","author":"Guo","year":"2014","journal-title":"J. Appl. Meteor. Sci."},{"key":"ref_41","first-page":"1","article-title":"Barrier\u2013corridor effect of longitudinal range\u2013gorge terrain on monsoons in Southwest China","volume":"31","author":"Wu","year":"2012","journal-title":"Geogr. Res."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1071\/WF12163","article-title":"Characterizing vegetative biomass burning in China using MODIS data","volume":"23","author":"Qin","year":"2014","journal-title":"Int. J. Wildland Fire"},{"key":"ref_43","unstructured":"(2019, December 14). U.S. National Aeronautics and Space Administration, Available online: https:\/\/search.earthdata.nasa.gov."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.gloplacha.2006.07.015","article-title":"Reconstruction of fire spread within wildland fire events in Northern Eurasia from the MODIS active fire product","volume":"56","author":"Loboda","year":"2007","journal-title":"Glob. Planet. Chang."},{"key":"ref_45","unstructured":"(2019, December 14). Consultative Group for International Agricultural Research: Consortium for Spatial Information (CGIAR-CSI). Available online: http:\/\/srtm.csi.cgiar.org."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1029\/EO081i048p00583","article-title":"Shuttle radar topography mission produces a wealth of data","volume":"81","author":"Farr","year":"2000","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.rse.2012.10.020","article-title":"A sub\u2013pixel\u2013based calculate of fire radiative power from MODIS observations: 2 Sensitivity analysis and potential fire weather application","volume":"129","author":"Peterson","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1080\/02693799508902045","article-title":"Interpolating mean rainfall using thin plate smoothing splines","volume":"9","author":"Hutchinson","year":"1995","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3354\/cr021001","article-title":"A high\u2013resolution data set of surface climate over global land areas","volume":"21","author":"New","year":"2002","journal-title":"Clim. Res."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1965","DOI":"10.1002\/joc.1276","article-title":"Very high resolution interpolated climate surfaces for global land areas","volume":"25","author":"Hijmans","year":"2005","journal-title":"Int. J. Climatol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1369","DOI":"10.1002\/joc.1187","article-title":"Spatial interpolation of monthly mean climate data for China","volume":"25","author":"Hong","year":"2005","journal-title":"Int. J. Climatol."},{"key":"ref_52","first-page":"56","article-title":"Comparative analysis of three covariates methods in Thin\u2013Plate Smoothing Splines for interpolating precipitation","volume":"31","author":"Liu","year":"2012","journal-title":"Prog. Geog."},{"key":"ref_53","unstructured":"Hutchinson, M.F. (2004). Anusplin Version 4.3. Centre for Resource and Environmental Studies, The Australian National University."},{"key":"ref_54","unstructured":"(2019, December 14). National Earth System Science Data Center of China. Available online: http:\/\/www.geodata.cn."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1214\/aoms\/1177704472","article-title":"On estimation of a probability density function and mode","volume":"33","author":"Parzen","year":"1962","journal-title":"Ann. Math. Stat."},{"key":"ref_56","unstructured":"Cox, D.R., Isham, V., Keiding, N., Reid, N., and Tong, H. (1986). Density estimation for statistics and data analysis. Monographys on Statistics and Applied Probability, Chapman and Hall London."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2656","DOI":"10.1016\/j.rse.2007.12.008","article-title":"Detection rates of the MODIS active fire product in the United States","volume":"112","author":"Hawbaker","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.jenvman.2012.01.024","article-title":"A spatio\u2013temporal analysis of fire recurrence and extent for semi\u2013arid savanna ecosystems in Southern Africa using moderate\u2013resolution satellite imagery","volume":"100","author":"Pricope","year":"2012","journal-title":"J. Environ. Manag."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_60","first-page":"18","article-title":"Classification and regression by randomforest","volume":"2","author":"Liaw","year":"2002","journal-title":"R News"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203451","article-title":"Greedy function approximation: A gradient boosting machine","volume":"29","author":"Friedman","year":"2001","journal-title":"Ann. Stat."},{"key":"ref_62","first-page":"213","article-title":"Environmental pollution when burning associated petroleum gas on the territory of oil producing enterprises","volume":"22","author":"Altunina","year":"2014","journal-title":"Chem. Sustain. Dev."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1016\/j.rse.2008.10.006","article-title":"An active-fire based burned area mapping algorithm for the MODIS sensor","volume":"113","author":"Giglio","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.isprsjprs.2012.11.005","article-title":"Sensitivity of the MODIS fire detection algorithm (MOD14) in the savanna region of the Northern Territory, Australia","volume":"76","author":"Maier","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1002\/joc.4680","article-title":"Daily synoptic conditions associated with large fire occurrence in Mediterranean France: Evidence for a wind-driven fire regime","volume":"37","author":"Ruffault","year":"2017","journal-title":"Int. J. Climatol."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Ye, T., Wang, Y., Guo, Z., and Li, Y. (2017). Factor contribution to fire occurrence, size, and burn probability in a subtropical coniferous forest in East China. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0172110"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1071\/WF13015","article-title":"Mapping the daily progression of large wildland fires using MODIS active fire data","volume":"23","author":"Veraverbeke","year":"2013","journal-title":"Int. J. Wildland Fire"},{"key":"ref_68","first-page":"2313","article-title":"Development and application of the WRFPLUS-Chem online chemistry adjoint and WRFDA-Chem assimilation system","volume":"8","author":"Guerrette","year":"2015","journal-title":"Geosci. Model Dev. Discuss."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"7155","DOI":"10.5194\/acp-15-7155-2015","article-title":"Fire emission heights in the climate system\u2014Part 1: Global plume height patterns simulated by ECHAM6\u2013HAM2","volume":"15","author":"Veira","year":"2015","journal-title":"Atmos. Chem. Phys."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"2411","DOI":"10.5194\/gmd-7-2411-2014","article-title":"Improved simulation of fire\u2013vegetation interactions in the Land surface Processes and eXchanges dynamic global vegetation model (LPX\u2013Mv1)","volume":"7","author":"Kelley","year":"2014","journal-title":"Geosci. Model Dev."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/24\/3031\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:42:40Z","timestamp":1760190160000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/24\/3031"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,16]]},"references-count":70,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2019,12]]}},"alternative-id":["rs11243031"],"URL":"https:\/\/doi.org\/10.3390\/rs11243031","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,12,16]]}}}